Recent Worthwhile Listens on TWIML

by Nathan Lasnoski

TWIML has long been one of my favorite podcasts (right after Crushing Iron… long story, different topic) and three recent ones I thought were particularly interesting. I think what makes TWIML great in general is how real the conversations are… it doesn’t feel like a boring interview. The topics are genuinely thought provoking and makes you want to understand more about how we think about the scenarios of AI.

The first I’d recommend was the most recent, Robert Ozawua talking about Causality. The most interesting thing he said (if i’m interpreting this right) was around how it’s essentially impossible to do ML without knowingly or unknowingly thinking about causality. In some cases the very action of building and using a model alters the causality of the situation. This is something I didn’t think about in quite that way before.

The second I’d recommend is a “year in review” of Ethics of AI by Timnit Gebru. I initially skipped the podcast, as I’ve heard a lot of Ethics of AI talks recently, but went back to it and was surprised by some of the interesting takes. In particular I appreciated how she talked about inclusion in the AI community itself and how it is our responsibility to drive engagement, especially for me, a middle-aged white guy born in privilege. I also appreciated how she talked about how the consciousness regarding AI ethics in general is being raised beyond “you should do this” to “how should you do this” and “should you do this”. Definitely worth the listen.

The third was Trends in Reinforcement Learning with Chelsea Finn, which covered a broad number of themes across reinforcement learning in 2019. I particularly found interesting where she talked about the “tag” experiments, as I had followed that for a while. Also themes in transfer learning, “God mode” starting over, and “remembering the video game” in this space, since that is critical to build effective platforms (we can’t just have a real car crash 1,000 times for it to learn how to do something). Just a great and very articulate understanding of what is going on.